Sample output files for tximport

This data package provides a set of output files from running a number of various transcript abundance quantifiers on 2 samples from the GEUVADIS Project (6 samples for Cufflinks), as well as a number of other datasets described below. The files are contained in the inst/extdata directory.

A citation for the GEUVADIS Project is:

Lappalainen, et al., “Transcriptome and genome sequencing uncovers functional variation in humans”, Nature 501, 506-511 (26 September 2013) doi:10.1038/nature12531.

The purpose of this vignette is to detail which versions of software were run, and exactly what calls were made.

Inferential replicate data moved to Zenodo

Previous versions of this package included Salmon Gibbs samples (salmon_gibbs) and kallisto bootstrap samples (kallisto_boot), as well as all 6 GEUVADIS samples for each quantifier, the GENCODE v48 GTF file, and other larger files. To reduce the size of the package, these were removed in version 1.41.1. The full set of files is archived on Zenodo:

https://doi.org/10.5281/zenodo.22982575

Sample information and quantification files

A small file, samples.txt is included in the inst/extdata directory:

dir <- system.file("extdata", package="tximportData")
samples <- read.table(file.path(dir,"samples.txt"), header=TRUE)
samples
##   pop center                assay    sample experiment       run
## 1 TSI  UNIGE NA20504.1.M_111124_7 ERS185242  ERX162972 ERR188088
## 2 TSI  UNIGE NA20508.1.M_111124_2 ERS185362  ERX163159 ERR188021

Further details can be found in a more extended table:

samples.ext <- read.delim(file.path(dir,"samples_extended.txt"), header=TRUE)
colnames(samples.ext)
##  [1] "Source.Name"                            
##  [2] "Comment.ENA_SAMPLE."                    
##  [3] "Characteristics.Organism."              
##  [4] "Term.Source.REF"                        
##  [5] "Term.Accession.Number"                  
##  [6] "Characteristics.Strain."                
##  [7] "Characteristics.population."            
##  [8] "Comment.1000g.Phase1.Genotypes."        
##  [9] "Protocol.REF"                           
## [10] "Protocol.REF.1"                         
## [11] "Extract.Name"                           
## [12] "Comment.LIBRARY_SELECTION."             
## [13] "Comment.LIBRARY_SOURCE."                
## [14] "Comment.SEQUENCE_LENGTH."               
## [15] "Comment.LIBRARY_STRATEGY."              
## [16] "Comment.LIBRARY_LAYOUT."                
## [17] "Comment.NOMINAL_LENGTH."                
## [18] "Comment.NOMINAL_SDEV."                  
## [19] "Protocol.REF.2"                         
## [20] "Performer"                              
## [21] "Assay.Name"                             
## [22] "Technology.Type"                        
## [23] "Comment.ENA_EXPERIMENT."                
## [24] "Comment.READ_INDEX_1_BASE_COORD."       
## [25] "Protocol.REF.3"                         
## [26] "Scan.Name"                              
## [27] "Comment.SUBMITTED_FILE_NAME."           
## [28] "Comment.ENA_RUN."                       
## [29] "Comment.FASTQ_URI."                     
## [30] "Protocol.REF.4"                         
## [31] "Derived.Array.Data.File"                
## [32] "Comment..Derived.ArrayExpress.FTP.file."
## [33] "Factor.Value.population."               
## [34] "Factor.Value.laboratory."               
## [35] "date"

The quantification outputs themselves can be found in sub-directories:

list.files(dir)
##  [1] "alevin"                  "cufflinks"              
##  [3] "kallisto"                "oarfish"                
##  [5] "refseq"                  "rsem"                   
##  [7] "sailfish"                "salmon"                 
##  [9] "salmon_dm"               "salmon_ec"              
## [11] "samples_extended.txt"    "samples.txt"            
## [13] "tx2gene_alevin.tsv"      "tx2gene.csv"            
## [15] "tx2gene.gencode.v27.csv"
list.files(file.path(dir,"cufflinks"))
## [1] "isoforms.attr_table"  "isoforms.count_table" "isoforms.fpkm_table"
list.files(file.path(dir,"rsem","ERR188021"))
## [1] "ERR188021.genes.results.gz"    "ERR188021.isoforms.results.gz"
list.files(file.path(dir,"kallisto","ERR188021"))
## [1] "abundance.tsv.gz" "run_info.json"
list.files(file.path(dir,"salmon","ERR188021"))
## [1] "aux_info"               "cmd_info.json"          "lib_format_counts.json"
## [4] "libParams"              "logs"                   "quant.sf.gz"
list.files(file.path(dir,"sailfish","ERR188021"))
## [1] "cmd_info.json" "quant.sf"
list.files(file.path(dir,"alevin"))
## [1] "mouse1_LPS2_50"      "mouse1_unst_50"      "mouse1_unst_50_boot"

Genome and gene annotation file

  • For Cufflinks and Sailfish, the Illumina iGenomes was used as the index, see details below.
  • For RSEM, Salmon and kallisto, the Gencode v27 CHR transcripts were used (gencode.v27.transcripts.fa).
  • For the salmon_dm directory, the Ensembl Drosophila melanogaster v92 transcripts were used (either just cDNA or combining cDNA with non-coding transcripts).

Illumina iGenomes: The human genome and annotations were downloaded from Illumina iGenomes for the UCSC hg19 version. The human genome FASTA file used was in the Sequence/WholeGenomeFasta directory and the gene annotation GTF file used was the genes.gtf file in the Annotation/Genes directory. This GTF file contains RefSeq transcript IDs and UCSC gene names. The Annotation directory contained a README.txt file with the text:

The contents of the annotation directories were downloaded from UCSC on: June 02, 2014.

The genes.gtf file was filtered to include only chromosomes 1-22, X, Y, and M.

RSEM

RSEM version 1.2.31 was run with the call:

rsem-calculate-expression --num-threads 6 --bowtie2 --paired-end <(zcat fastq/$f\_1.fastq.gz) <(zcat fastq/$f\_2.fastq.gz) index rsem/$f/$f

kallisto

kallisto version 0.43.1 was run with the call:

kallisto quant --bias -i index -t 6 -o kallisto/$f fastq/$f\_1.fastq.gz fastq/$f\_2.fastq.gz

Only the abundance.tsv.gz files are included (these runs have no bootstrap samples).

Salmon

Salmon version 0.8.2 was run with the call:

salmon quant -p 6 --gcBias -i index -l IU -1 fastq/$f\_1.fastq.gz -2 fastq/$f\_2.fastq.gz -o salmon/$f

For the files in the salmon_dm directory (Drosophila melanogaster), Salmon version 0.10.2 was run (once with only cDNA, once combining cDNA with non-coding transcripts):

salmon quant -l A --gcBias --seqBias --posBias -i Drosophila_melanogaster.BDGP6.cdna.v92_salmon_0.10.2 -o SRR1197474 -1 SRR1197474_1.fastq.gz -2 SRR1197474_2.fastq.gz

For the files in the salmon_ec directory, Salmon version 1.1.0 was run with --dumpEq on the files from Tasic, B., Yao, Z., Graybuck, L.T. et al. “Shared and distinct transcriptomic cell types across neocortical areas” (2018) doi: 10.1038/s41586-018-0654-5 These files were generated by Jeroen Gilis. The raw data is from: https://www.ncbi.nlm.nih.gov/Traces/study/?acc=PRJNA476008&o=acc_s%3Aa

alevin

Two small examples of alevin output (50 cells each) were generated by Jeroen Gilis. The dataset is a subset from the paper, Hagai et al. “Gene expression variability across cells and species shapes innate immunity” (2018) doi: 10.1038/s41586-018-0657-2 Salmon/alevin version 1.6.0 was run, and using the tx2gene data that is included in the package under tx2gene_alevin.tsv.

oarfish

Three samples were processed with oarfish v0.9.0, downloaded from the fastq download page of the SG-NEx Project. See also this GitHub page.

The samples were SGNex_H9_cDNA replicates 2-4, run 4.

These three samples were quantified with oarfish against human GENCODE v48 supplemented with “novel” sequences of length 1,000 bp across chr1-22 (500 per chromosome = 11,000 new transcripts named novel1, novel2, …).

Code for the quantification steps are posted to a GitHub repo.

Briefly the following lines were used:

oarfish --only-index --annotated gencode.v48.transcripts.fa.gz --novel novel.fa.gz --seq-tech ont-cdna --threads 32 --index-out gencode_plus_novel
oarfish --reads reads/SGNex_H9_cDNA_replicateXYZ_run4.fastq.gz --index gencode_plus_novel --output quants/sgnex_h9_rep2 --seq-tech ont-cdna --filter-group no-filters --threads 32

Citation for the SG-NEx Project:

Chen, Y., Davidson, N.M., Wan, Y.K. et al. A systematic benchmark of Nanopore long-read RNA sequencing for transcript-level analysis in human cell lines. Nat Methods 22, 801–812 (2025). https://doi.org/10.1038/s41592-025-02623-4

Sailfish

Sailfish version 0.9.0 was run with the call:

sailfish quant -p 10 --biasCorrect -i sailfish_0.9.0/index -l IU -1 <(zcat fastq/$f\_1.fastq.gz) -2 <(zcat fastq/$f\_2.fastq.gz) -o sailfish_0.9.0/$f

Session info

sessionInfo()
## R version 4.6.1 (2026-06-24)
## Platform: x86_64-pc-linux-gnu
## Running under: Ubuntu 26.04.1 LTS
## 
## Matrix products: default
## BLAS:   /usr/lib/x86_64-linux-gnu/openblas-pthread/libblas.so.3 
## LAPACK: /usr/lib/x86_64-linux-gnu/openblas-pthread/libopenblasp-r0.3.32.so;  LAPACK version 3.12.0
## 
## locale:
##  [1] LC_CTYPE=en_US.UTF-8       LC_NUMERIC=C              
##  [3] LC_TIME=en_US.UTF-8        LC_COLLATE=en_US.UTF-8    
##  [5] LC_MONETARY=en_US.UTF-8    LC_MESSAGES=en_US.UTF-8   
##  [7] LC_PAPER=en_US.UTF-8       LC_NAME=C                 
##  [9] LC_ADDRESS=C               LC_TELEPHONE=C            
## [11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C       
## 
## time zone: Etc/UTC
## tzcode source: system (glibc)
## 
## attached base packages:
## [1] stats     graphics  grDevices utils     datasets  methods   base     
## 
## loaded via a namespace (and not attached):
##  [1] digest_0.6.39    R6_2.6.1         fastmap_1.2.0    xfun_0.61       
##  [5] maketools_1.3.2  cachem_1.1.0     knitr_1.52       htmltools_0.5.9 
##  [9] rmarkdown_2.32   buildtools_1.0.0 lifecycle_1.0.5  cli_3.6.6       
## [13] sass_0.4.10      jquerylib_0.1.4  compiler_4.6.1   sys_3.4.3       
## [17] tools_4.6.1      evaluate_1.0.5   bslib_0.12.0     jsonlite_2.0.0  
## [21] rlang_1.3.0